Ethics vs. Regulation: Converging Frameworks for Trustworthy Human-Centered AI in Biomedical Research

Abstract

The accelerating impact of AI in biomedical research is driving significant advances in precision medicine. As these systems increasingly shape health outcomes, the imperative to develop trustworthy, reliable, and ethically grounded AI becomes more pressing, particularly in addressing concerns related to data integrity, patient safety, and equitable outcomes. While the potential of AI to transform biomedical research is clear, its responsible integration depends on more than technological capability. Ensuring that these systems are aligned with societal values requires a dual commitment: the operationalization of ethical principles throughout the AI life cycle and the establishment of robust regulatory mechanisms. Ethics provides the normative vision for fairness, accountability, and human dignity, whereas regulation translates these ideals into enforceable standards. This paper explores the convergence of these domains as a necessary foundation for developing trustworthy human-centered AI in biomedical contexts. We provide practical guidance for AI developers and researchers on integrating proactive governance and translating ethical principles into actionable strategies to support equitable and responsible innovation.

Department(s)

Cooperative Engineering Program

Document Type

Conference Proceeding

DOI

10.1109/IJCNN64981.2025.11227432

Keywords

AI governance, biomedical AI Ethics, human-centered AI, regulatory frameworks, trustworthy AI

Publication Date

1-1-2025

Journal Title

Proceedings of the International Joint Conference on Neural Networks

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